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词条 Pixel Visual Core
释义

  1. History

  2. SR3HX Design

  3. See also

  4. References

The Pixel Visual Core (PVC) co-processors are a series of ARM-based System in Package (SiP) image processors designed by Google.[1] The PVC is a fully programmable Image, Vision and AI processor for mobile devices. It first appeared in the Google Pixel 2 and 2 XL which were introduced on October 19, 2017. It has also appeared in the Google Pixel 3 and 3 XL.

History

Google previously used Qualcomm Snapdragon's CPU, GPU, IPU, and DSP to handle their image processing for their Google Nexus and Google Pixel devices. With the increasing importance of computational photography techniques, Google developed the Pixel Visual Core (PVC). Google claims the PVC uses less power than using CPU and GPU while still being fully programmable, unlike their Tensor processing unit (TPU) application-specific integrated circuit (ASIC).

The PVC in the Google Pixel 2 and 2 XL is labeled SR3HX X726C502.[2]

The PVC in the Google Pixel 3 and 3 XL is labeled SR3HX X739F030.[3]

SR3HX Design

The SR3HX PVC features a 64-bit ARMv8a ARM Cortex-A53 CPU, 8x Image Processing Unit (IPU) cores, 512 MB LPDDR4, MIPI, PCIe. The IPU cores each have 512 Arithmetic Logic Units (ALUs) consisting of 256 processing elements (PEs) arranged as a 16 x 16 2-dimensional array. Those cores execute a custom VLIW ISA.There are two 16-bit ALUs per processing element and they can operate in three distinct ways: independent, joined, and fused.[4] The SR3HX PVC is manufactured as a SiP by TSMC using their 28HPM HKMG process.[1] It was design over 4 years in partnership with intel. (Codename : Monette Hill)[5] Google claim the SR3HX PVC is 7-16x more energy-efficient than the Snapdragon 835.[1] And that the SR3HX PVC can perform 3 trillion operations per second, HDR+ can run 5x faster and at less than one-tenth the energy than the Snapdragon 835.[6] It supports Halide for image processing and TensorFlow for machine learning.[6] At 800 MHz, the chip is capable of 4,096 FLOPs/cycle (2*16*16*8) or 3.28 TeraFLOPS of raw compute power.[4]

See also

  • Google Pixel devices, range of consumer hardware designed by Google
  • Tensor processing unit (TPU), Google design ASICs for neural network machine learning processing.

References

1. ^{{Cite web|url=https://www.anandtech.com/show/13241/hot-chips-2018-the-google-pixel-visual-core-live-blog|title=Hot Chips 2018: The Google Pixel Visual Core Live Blog (10am PT, 5pm UTC)|last=Cutress|first=Ian|website=www.anandtech.com|access-date=2019-02-02}}
2. ^{{Cite web|url=https://www.ifixit.com/Teardown/Google+Pixel+2+XL+Teardown/98093|title=Google Pixel 2 XL Teardown|date=2017-10-19|website=iFixit|language=en|access-date=2019-02-02}}
3. ^{{Cite web|url=https://www.ifixit.com/Teardown/Google+Pixel+3+XL+Teardown/113656|title=Google Pixel 3 XL Teardown|date=2018-10-16|website=iFixit|language=en|access-date=2019-02-02}}
4. ^{{Cite web|url=https://en.wikichip.org/wiki/google/pixel_visual_core|title=Pixel Visual Core (PVC) - Google - WikiChip|website=en.wikichip.org|language=en|access-date=2019-02-02}}
5. ^{{Cite web|url=https://www.xda-developers.com/google-intel-pixel-visual-core-chip/|title=Google Partnered with Intel for the Pixel Visual Core Chip in the Pixel 2|date=2017-10-25|website=xda-developers|language=en-US|access-date=2019-02-02}}
6. ^{{Cite web|url=https://www.blog.google/products/pixel/pixel-visual-core-image-processing-and-machine-learning-pixel-2/|title=Pixel Visual Core: image processing and machine learning on Pixel 2|date=2017-10-17|website=Google|language=en|access-date=2019-02-02}}

2 : Google hardware|Application-specific integrated circuits

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